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Image-based Displacement Identification (IDI) implementation in python.
See the documentation for pyIDI
.
Create an instance:
video = pyidi.pyIDI(input_file='video.cih')
The pyIDI
method works with various formats: .cih
, .cihx
, .png
, .avi
etc. Additionally, it can also work with numpy.ndarray
as input.
If an array is passed, it must have a shape of: (n time points, image height, image width)
.
Set the points where displacements will be determined:
p = np.array([[0, 1], [1, 1], [2, 1]]) # example of points
video.set_points(points=p)
Or use point selection UI to set individual points or grid inside selected area. For more information about UI see documentation. Launch viewer with:
video.gui()
The method of identification has to be specified:
video.set_method(method='sof', **method_kwargs)
After points are set, displacements can be calculated (using method, set in set_method
):
displacements = video.get_displacements()
Multiprocessing can also be used by passing the processes
argument:
displacements = video.get_displacements(processes=4)
IDIMethods
calculate_displacements
with attribute displacements
get_points
(static method - sets attribute video.points)pyIDI
add a new method of identification in avaliable_methods
dictionary.If you are using the pyIDI
package for your research, consider citing our articles:
FAQs
Python Image Displacement Identification.
We found that pyidi demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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